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How can linguistic data collection methods be adapted to new technology?

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Linguistic data collection methods are essential for studying various aspects of language, such as phonetics, syntax, semantics, pragmatics, sociolinguistics, and more. However, traditional methods of collecting linguistic data, such as surveys, interviews, experiments, and corpora, may face some challenges and limitations in the era of new technology. How can linguistic data collection methods be adapted to new technology? In this article, you will learn about some examples of how linguists are using new technology to collect, analyze, and share linguistic data in innovative and efficient ways.

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Stefan Huyghe

??Localization VP ? AI Enterprise Strategist ?? LinkedIn B2B Growth ?Globalization Consultant ?? LangOps Pioneer…

1 Online platforms

One way of adapting linguistic data collection methods to new technology is to use online platforms that allow linguists to create and distribute surveys, experiments, and tasks to a large and diverse pool of participants. For example, platforms like Amazon Mechanical Turk, Prolific, and Qualtrics enable linguists to recruit and compensate participants, design and administer linguistic tasks, and collect and export data in various formats. Online platforms can also facilitate collaboration and communication among linguists and participants, as well as ethical and transparent research practices.

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Stefan Huyghe

??Localization VP ? AI Enterprise Strategist ?? LinkedIn B2B Growth ?Globalization Consultant ?? LangOps Pioneer ??Content Creator ?? Social Media Evangelist ?? Podcast Host ?? LocDiscussion Brainparent
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Linguistic data collection from online platforms can leverage a vast, diverse, and dynamic dataset. Automated Web Scraping, Crowdsourcing, and even targeted online survey experiments are worth a try because they allow us to capture real-time language use, slang, and emerging linguistic trends, offering a more comprehensive view of language usage across different demographics and regions. It still will require filtering to ensure relevance and quality. While these methods might be more cost-effective, they might also lack consistency in data quality. It also remains to be seen to be seen whether they enable us to target specific linguistic groups or demographics.

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2 Mobile devices

Another way of adapting linguistic data collection methods to new technology is to use mobile devices, such as smartphones, tablets, and wearable devices, that can capture and transmit linguistic data in real time and in natural settings. For example, mobile devices can be used to record and analyze speech, gesture, eye movement, and other multimodal cues that are relevant for linguistic research. Mobile devices can also be used to deliver linguistic stimuli and feedback, such as text, audio, video, or images, to participants in various contexts and situations.

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3 Social media

A third way of adapting linguistic data collection methods to new technology is to use social media as a source of linguistic data that reflects the diversity and dynamism of language use in online communication. For example, social media platforms, such as Twitter, Facebook, Instagram, and Reddit, provide linguists with access to large and rich datasets of text, audio, video, and images that can be used to study various linguistic phenomena, such as language variation, change, innovation, and identity. Social media data can also be used to investigate the interaction and influence of language and other social factors, such as gender, age, ethnicity, culture, and ideology.

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4 Artificial intelligence

A fourth way of adapting linguistic data collection methods to new technology is to use artificial intelligence (AI) as a tool for enhancing and automating linguistic data collection, analysis, and visualization. For example, AI techniques, such as machine learning, natural language processing, speech recognition, and computer vision, can be used to process and extract linguistic features, patterns, and insights from large and complex datasets. AI techniques can also be used to generate and evaluate linguistic data, such as synthetic speech, text, or images, that can be used for testing linguistic hypotheses or creating linguistic stimuli.

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5 Ethical issues

A final way of adapting linguistic data collection methods to new technology is to consider and address the ethical issues that may arise from using new technology for linguistic research. For example, ethical issues may include the privacy and consent of participants, the quality and validity of data, the bias and fairness of algorithms, and the social and cultural implications of linguistic findings. Linguists should follow the ethical guidelines and standards of their discipline and institutions, as well as the laws and regulations of the countries and regions where they conduct their research. Linguists should also respect and acknowledge the rights and interests of the linguistic communities and individuals who contribute to their research.

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Stefan Huyghe

??Localization VP ? AI Enterprise Strategist ?? LinkedIn B2B Growth ?Globalization Consultant ?? LangOps Pioneer ??Content Creator ?? Social Media Evangelist ?? Podcast Host ?? LocDiscussion Brainparent
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Robust data security measures are essential to protect sensitive data, and transparency in how linguistic data is collected, used, and shared is a key ethical obligation. This balance between innovation and ethical responsibility is crucial in ensuring that the collected data is not only extensive and diverse but also gathered and used in a manner that respects individual rights and societal norms. Part of the challenge will undoubtedly be that many of the laws that address AI and data collection are still being drawn up and adjusted. It is difficult to anticipate what will be allowed and what won't going forward.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Stefan Huyghe

??Localization VP ? AI Enterprise Strategist ?? LinkedIn B2B Growth ?Globalization Consultant ?? LangOps Pioneer ??Content Creator ?? Social Media Evangelist ?? Podcast Host ?? LocDiscussion Brainparent
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Considering the temporal aspect of language use is important. Language evolves over time, and real-time methods that allow for better tracking of these changes can provide valuable insights into linguistic trends and patterns. Additionally, in linguistic data, there will often be anomalies or non-standard uses of language. Developing methods to handle and interpret this data is also important for a comprehensive understanding of language use.

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How can linguistic data collection methods be adapted to new technology?

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1 Online platforms

2 Mobile devices

3 Social media

4 Artificial intelligence

5 Ethical issues

6 Here’s what else to consider

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